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Multiview photometric stereo (MVPS) seeks to recover high-fidelity surface shapes and reflectances from images captured under varying views and illuminations. However, existing MVPS methods often require controlled darkroom settings for…

Computer Vision and Pattern Recognition · Computer Science 2025-08-07 Songyun Yang , Yufei Han , Jilong Zhang , Kongming Liang , Peng Yu , Zhaowei Qu , Heng Guo

We propose a novel biophysical and dichromatic reflectance model that efficiently characterises spectral skin reflectance. We show how to fit the model to multispectral face images enabling high quality estimation of diffuse and specular…

Computer Vision and Pattern Recognition · Computer Science 2019-02-19 Sarah Alotaibi , William A. P. Smith

Facial geometry and appearance capture have demonstrated tremendous success in 3D scanning real humans in studios. Recent works propose to democratize this technique while keeping the results high quality. However, they are still…

Computer Vision and Pattern Recognition · Computer Science 2026-03-18 Yuxuan Han , Junfeng Lyu , Feng Xu

We present a differentiable framework to adaptively compute 4D illumination conditions with respect to an object, for efficient, high-quality simultaneous acquisition of its shape and reflectance, with a unified spatial-angular structured…

Computer Vision and Pattern Recognition · Computer Science 2026-05-08 Huakeng Ding , Yaowen Chen , Kun Zhou , Hongzhi Wu

In this study, we introduce a novel two-stage technique for decomposing and reconstructing facial features from sparse-view images, a task made challenging by the unique geometry and complex skin reflectance of each individual. To…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Daisheng Jin , Jiangbei Hu , Baixin Xu , Yuxin Dai , Chen Qian , Ying He

Fine-detailed reconstructions are in high demand in many applications. However, most of the existing RGB-D reconstruction methods rely on pre-calculated accurate camera poses to recover the detailed surface geometry, where the…

Computer Vision and Pattern Recognition · Computer Science 2022-10-25 Lu Sang , Bjoern Haefner , Xingxing Zuo , Daniel Cremers

Designing a network on 3D surface for non-rigid shape analysis is a challenging task. In this work, we propose a novel spectral transform network on 3D surface to learn shape descriptors. The proposed network architecture consists of four…

Computer Vision and Pattern Recognition · Computer Science 2018-10-23 Ruixuan Yu , Jian Sun , Huibin Li

In this paper, we present a technique for estimating the geometry and reflectance of objects using only a camera, flashlight, and optionally a tripod. We propose a simple data capture technique in which the user goes around the object,…

Computer Vision and Pattern Recognition · Computer Science 2021-04-14 Daniel Lichy , Jiaye Wu , Soumyadip Sengupta , David W. Jacobs

This paper presents a process for estimating the spatially varying surface reflectance of complex scenes observed under natural illumination. In contrast to previous methods, our process is not limited to scenes viewed under controlled…

Computer Vision and Pattern Recognition · Computer Science 2022-03-01 Alen Joy , Charalambos Poullis

High-precision laser interferometric instruments require optical surfaces with a close to perfect contour, as well as low scattering and absorption. Especially point absorbers are problematic because they heat up at high optical intensities…

Optics · Physics 2023-12-20 Leif Albers , Malte Hagemann , Roman Schnabel

Photometric stereo is a technique for estimating surface normals using images captured under varying illumination. However, conventional frame-based photometric stereo methods are limited in real-world applications due to their reliance on…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Hyunwoo Kim , Won-Hoe Kim , Sanghoon Lee , Jianfei Cai , Giljoo Nam , Jae-Sang Hyun

This paper proposes an uncalibrated photometric stereo method for non-Lambertian scenes based on deep learning. Unlike previous approaches that heavily rely on assumptions of specific reflectances and light source distributions, our method…

Computer Vision and Pattern Recognition · Computer Science 2019-03-19 Guanying Chen , Kai Han , Boxin Shi , Yasuyuki Matsushita , Kwan-Yee K. Wong

We present Neural Microfacet Fields, a method for recovering materials, geometry, and environment illumination from images of a scene. Our method uses a microfacet reflectance model within a volumetric setting by treating each sample along…

Computer Vision and Pattern Recognition · Computer Science 2023-10-18 Alexander Mai , Dor Verbin , Falko Kuester , Sara Fridovich-Keil

This paper introduces a versatile paradigm for integrating multi-view reflectance (optional) and normal maps acquired through photometric stereo. Our approach employs a pixel-wise joint re-parameterization of reflectance and normal,…

Computer Vision and Pattern Recognition · Computer Science 2024-04-01 Baptiste Brument , Robin Bruneau , Yvain Quéau , Jean Mélou , François Bernard Lauze , Jean-Denis , Jean-Denis Durou , Lilian Calvet

We propose a method for estimating high-definition spatially-varying lighting, reflectance, and geometry of a scene from 360$^{\circ}$ stereo images. Our model takes advantage of the 360$^{\circ}$ input to observe the entire scene with…

Computer Vision and Pattern Recognition · Computer Science 2021-04-21 Junxuan Li , Hongdong Li , Yasuyuki Matsushita

We present a novel convolutional neural network architecture for photometric stereo (Woodham, 1980), a problem of recovering 3D object surface normals from multiple images observed under varying illuminations. Despite its long history in…

Computer Vision and Pattern Recognition · Computer Science 2018-05-30 Tatsunori Taniai , Takanori Maehara

Label-free microscopy exploits light scattering to obtain a three-dimensional image of biological tissues. However, light propagation is affected by aberrations and multiple scattering, which drastically degrade the image quality and limit…

The problem of estimating a surface shape from its observed reflectance properties still remains a challenging task in computer vision. The presence of global illumination effects such as inter-reflections or cast shadows makes the task…

Computer Vision and Pattern Recognition · Computer Science 2021-03-24 David Honzátko , Engin Türetken , Pascal Fua , L. Andrea Dunbar

Simultaneous reconstruction of geometry and reflectance properties in uncontrolled environments remains a challenging problem. In this paper, we propose an efficient method to reconstruct the scene's 3D geometry and reflectance from…

Computer Vision and Pattern Recognition · Computer Science 2022-03-01 Rui Li , Guangmin Zang , Miao Qi , Wolfgang Heidrich

We consider the problem of few-viewpoint 3D surface reconstruction using raw measurements from a lidar system. Lidar captures 3D scene geometry by emitting pulses of light to a target and recording the speed-of-light time delay of the…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Weihan Luo , Anagh Malik , David B. Lindell